# nietras/Sep

World's Fastest .NET CSV Parser. Modern, minimal, fast, zero allocation, reading and writing of separated values (`csv`, `tsv` etc.). Cross-platform, trimmable and AOT/NativeAOT compatible with blazing fast SIMD vectorized parsing.

Repository: https://github.com/nietras/Sep
Canonical: https://ross.abutalabs.com/products/sep
Homepage: http://nietras.com
Language: C#
License: MIT
License Family: permissive
Topics: csharp, csv, csv-parser, csv-reader, csv-writer, dotnet, performance, simd
Last push: 2026-08-17T14:49:23+00:00

## Health v2 (maintenance only)
Score: 97/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 98, release rhythm 98, longevity 92
- inputs: {"age_days": 1294, "days_push": 16, "days_rel": 16, "gap_med": 17.5, "n_releases_24m": 29}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1467, forks 53 (observed 2026-08-28T04:04:48.825910+00:00)

## What it is
Sep is a modern, minimal .NET library for reading and writing separated values (CSV, TSV, etc.) with zero allocations and SIMD-vectorized parsing. It targets machine learning and data pipeline use cases and is cross-platform, trimmable, and AOT/NativeAOT compatible.

## Use cases
- parse large csv files fast in .net
- read tsv files with zero allocations
- write csv files in c#
- load machine learning datasets from csv
- high performance csv parsing with simd
- multithreaded csv parsing in dotnet

## When to choose
- you need maximum CSV/TSV parsing throughput in .NET
- you want zero-allocation, AOT-compatible parsing for ML pipelines
- you prefer a minimal, opinionated API over configurable CSV readers

## When to avoid
- you need extensive CSV dialect options, automatic escaping, or RFC 4180 edge-case handling out of the box
- you are not on .NET 7+ / C# 11+
- you need a full data manipulation library rather than a parser

## Facets
- artifact type: library
- maturity: active
- function: parser, serialization, data-science
- domain: files, data-science, developer-tools, machine-learning
- platform: dotnet, cross-platform
- tags: csv, tsv, simd, zero-allocation, performance, separated-values

## Member repositories
- nietras/Sep (main) score 97

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:48.825910+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T04:35:00.952343+00:00, confidence not recorded.
  - readme: https://github.com/nietras/Sep (fetched 2026-08-28T04:04:48.825910+00:00, sha 27c93d6630aa)
  - homepage: http://nietras.com (fetched 2026-08-29T11:43:09.304017+00:00, sha cf611f7c8e89)
  - site_page: https://nietras.com/about (fetched 2026-08-29T11:43:09.313781+00:00, sha 108c513a45bd)
- Data as of 2026-08-30T08:39:29.467469+00:00.